Doctoral Dissertations

Huchun

Keywords and Phrases

Power Usage Control; Privacy-preserving; Smart Grid

Abstract

"The smart grid (SG) has been emerging as the next-generation intelligent power grid system because of its ability to efficiently monitor, predicate, and control energy generation, transmission, and consumption by analyzing users' real-time electricity information. Consider a situation in which the utility company would like to smartly protect against a power outage. To do so, the company can determine a threshold for a neighborhood. Whenever the total power usage from the neighborhood exceeds the threshold, some or all of the households need to reduce their energy consumption to avoid the possibility of a power outage. This problem is referred to as threshold-based power usage control (TPUC) in the literature. In order to solve the TPUC problem, the utility company is required to periodically collect the power usage data of households. However, it has been well documented that these power usage data can reveal consumers' daily activities and violate personal privacy. To avoid the privacy concerns, privacy-preserving power usage control (P-PUC) protocols are proposed under two strategies: adjustment based on maximum power usage and adjustment based on individual power usage. These protocols allow a utility company to manage power consumption effectively and at the same time, preserve the privacy of all involved parties. Furthermore, the practical value of the proposed protocols is empirically shown through various experiments"--Abstract, page iii.

Advisor(s)

Jiang, Wei

Committee Member(s)

McMillin, Bruce M.
Cheng, Maggie Xiaoyan
Lin, Dan
Wen, Xuerong Meggie

Department(s)

Computer Science

Degree Name

Ph. D. in Computer Science

Publisher

Missouri University of Science and Technology

Publication Date

2015

Pagination

ix, 87 pages

Note about bibliography

Includes bibliographic references (pages 80-86).

Rights

© 2015 Huchun, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 11144

Electronic OCLC #

1003210396

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